For this ARRA RFA-OD-09-004 GO application, we propose to perform an integrated genome-wide mutational analysis of oral cancers using high throughput sequence analysis of coding genes combined with analyses of copy number, gene expression, and methylation. Genetic alterations represent the underlying cause of human cancer, including tumors of the oral cavity. In the United States, oral cancers represent ~50% of the 46,000 cases of head and neck cancers. Oral cancer affects physical appearance and vital functions, including taste, swallowing, and speech/phonation. In addition to significant morbidity, head and neck cancer result in ~12,000 deaths, of which oral cancer will be responsible for ~5,400 deaths. Given the significant morbidity and mortality of these tumors, there is a profound need for novel clinical approaches for oral cancer. This project will identify potential new avenues for therapeutic, diagnostic and prognostic intervention in oral cancer, and will serve as a model for genomic analyses of other head and neck cancers. For mutational screening, we will employ the two stage, high throughput DNA sequencing approach that we have recently refined and used to identify novel tumor-relevant mutations in breast, colon, pancreatic, and glioblastoma tumors. This strategy significantly increases the power and reduces the cost of large scale tumor sequencing, providing highly sensitive mutational analysis of >95% of bases of ~200,000 exons from over 20,000 coding genes. In the first stage of this approach, exon sequencing analysis will be performed on a set of 24 clinically annotated oral cancer samples. All mutations will be examined in a normal DNA sample from the same patient to identify and confirm tumor-specific mutations. In the second stage, the mutated genes will be analyzed by sequencing a larger set of at least 48 tumors. Previously developed biostatistical criteria will be applied to discriminate between tumor-relevant driver and irrelevant passenger mutations. In the same set of oral cancer samples examined for mutations, we will also perform copy number analysis using high density SNP microarrays, gene expression analysis by combination of next generation sequencing and serial analysis of gene expression (SAGE), and gene methylation analysis by Infinium methylation microarrays. Bioinformatics analyses will integrate these findings with mutational data, following a signaling pathways perspective that has proved to be powerful in our recent studies. Our hypothesis, based on experience in other tumor types, is that copy number changes and expression loss by promoter methylation, acting in concert with mutations, will be enriched in pathways that are important for development of oral cancer. As has been the case in other cancer types, identification of these altered signaling pathways is likely to provide potential therapeutic strategies for oral cancer. This grant is expected to have a significant economic effect, resulting in the employment of individuals performing genomic research on oral cancer and in subsequent studies of head and neck cancers in general. PUBLIC HEALTH RELEVANCE: We propose to perform an integrated genome-wide mutational analysis of oral cancers using high throughput sequence analysis of coding genes combined with analyses of copy number, gene expression, and methylation.